Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper.

Training machine learning models using data from severe COVID-19 patients admitted to a central hosp...

Development of an mPBPK machine learning framework for early target pharmacology assessment of biotherapeutics.

Development of antibodies often begins with the assessment and optimization of their physicochemical...

Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning.

To develop a deep learning model using transfer learning for automatic detection and segmentation of...

Machine Learning and Experiments Revealed Key Genes Related to PANoptosis Linked to Drug Prediction and Immune Landscape in Spinal Cord Injury.

Spinal cord injury (SCI) is a severe central nervous system injury without effective therapies. PANo...

The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.

This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in...

Machine Learning-Powered Optimization of a CHO Cell Cultivation Process.

Chinese Hamster Ovary (CHO) cells are the most widely used cell lines to produce recombinant therape...

Synergistic modeling of hemorrhagic dengue fever: Passive immunity dynamics and time-delay neural network analysis.

Dengue fever poses a formidable epidemiological challenge, particularly for vulnerable groups such a...

Semi-supervised learning-based identification of the attachment between sludge and microparticles in wastewater treatment.

Monitoring the microparticle transfer process in wastewater treatment systems is crucial for improvi...

Accessible halitosis diagnosis: validating the accuracy of novel AI-based compact VSC measuring instrument.

Halitosis presents a significant global health concern, necessitating the development of precise and...

Self-supervised 3D medical image segmentation by flow-guided mask propagation learning.

Despite significant progress in 3D medical image segmentation using deep learning, manual annotation...

Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing.

BACKGROUND: Amebiasis represents a significant global health concern. This is especially evident in ...

Comparative Analysis of Machine Learning Algorithms Used for Translating Aptamer-Antigen Binding Kinetic Profiles to Diagnostic Decisions.

Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds b...

Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization.

In 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems o...

Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.

Accurately predicting activation energies is crucial for understanding chemical reactions and modeli...

Deep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach.

We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparame...

Ultrasensitive Detection of Circulating Plasma Cells Using Surface-Enhanced Raman Spectroscopy and Machine Learning for Multiple Myeloma Monitoring.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma c...

Deep-Learning-Assisted Digital Fluorescence Immunoassay on Magnetic Beads for Ultrasensitive Determination of Protein Biomarkers.

Digital fluorescence immunoassay (DFI) based on random dispersion magnetic beads (MBs) is one of the...

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